From a64fe4d083173cc67dd7585c3160a94ea24bca80 Mon Sep 17 00:00:00 2001
From: Daniil Kazantsev <dkazanc@hotmail.com>
Date: Wed, 2 May 2018 10:06:38 +0100
Subject: cyth corr
---
Wrappers/Python/src/cpu_regularisers.pyx | 13 ++++++-------
Wrappers/Python/src/gpu_regularisers.pyx | 10 +++++-----
2 files changed, 11 insertions(+), 12 deletions(-)
(limited to 'Wrappers/Python/src')
diff --git a/Wrappers/Python/src/cpu_regularisers.pyx b/Wrappers/Python/src/cpu_regularisers.pyx
index 21a1a00..7c06c28 100644
--- a/Wrappers/Python/src/cpu_regularisers.pyx
+++ b/Wrappers/Python/src/cpu_regularisers.pyx
@@ -102,7 +102,7 @@ def TV_FGP_2D(np.ndarray[np.float32_t, ndim=2, mode="c"] inputData,
methodTV,
nonneg,
printM,
- dims[0], dims[1], 1)
+ dims[1],dims[0],1)
return outputData
@@ -161,7 +161,7 @@ def TV_SB_2D(np.ndarray[np.float32_t, ndim=2, mode="c"] inputData,
tolerance_param,
methodTV,
printM,
- dims[0], dims[1], 1)
+ dims[1],dims[0],1)
return outputData
@@ -222,7 +222,7 @@ def dTV_FGP_2D(np.ndarray[np.float32_t, ndim=2, mode="c"] inputData,
methodTV,
nonneg,
printM,
- dims[0], dims[1], 1)
+ dims[1], dims[0], 1)
return outputData
@@ -301,7 +301,7 @@ def NDF_2D(np.ndarray[np.float32_t, ndim=2, mode="c"] inputData,
np.zeros([dims[0],dims[1]], dtype='float32')
# Run Nonlinear Diffusion iterations for 2D data
- Diffusion_CPU_main(&inputData[0,0], &outputData[0,0], regularisation_parameter, edge_parameter, iterationsNumb, time_marching_parameter, penalty_type, dims[0], dims[1], 1)
+ Diffusion_CPU_main(&inputData[0,0], &outputData[0,0], regularisation_parameter, edge_parameter, iterationsNumb, time_marching_parameter, penalty_type, dims[1], dims[0], 1)
return outputData
def NDF_3D(np.ndarray[np.float32_t, ndim=3, mode="c"] inputData,
@@ -349,7 +349,7 @@ def NDF_INP_2D(np.ndarray[np.float32_t, ndim=2, mode="c"] inputData,
np.zeros([dims[0],dims[1]], dtype='float32')
# Run Inpaiting by Diffusion iterations for 2D data
- Diffusion_Inpaint_CPU_main(&inputData[0,0], &maskData[0,0], &outputData[0,0], regularisation_parameter, edge_parameter, iterationsNumb, time_marching_parameter, penalty_type, dims[0], dims[1], 1)
+ Diffusion_Inpaint_CPU_main(&inputData[0,0], &maskData[0,0], &outputData[0,0], regularisation_parameter, edge_parameter, iterationsNumb, time_marching_parameter, penalty_type, dims[1], dims[0], 1)
return outputData
def NDF_INP_3D(np.ndarray[np.float32_t, ndim=3, mode="c"] inputData,
@@ -396,7 +396,6 @@ def NVM_INP_2D(np.ndarray[np.float32_t, ndim=2, mode="c"] inputData,
# Run Inpaiting by Nonlocal vertical marching method for 2D data
NonlocalMarching_Inpaint_main(&inputData[0,0], &maskData[0,0], &outputData[0,0], &maskData_upd[0,0],
- SW_increment, iterationsNumb,
- dims[0], dims[1], 1)
+ SW_increment, iterationsNumb,dims[1], dims[0], 1)
return (outputData, maskData_upd)
diff --git a/Wrappers/Python/src/gpu_regularisers.pyx b/Wrappers/Python/src/gpu_regularisers.pyx
index b0775054..7eab5d5 100644
--- a/Wrappers/Python/src/gpu_regularisers.pyx
+++ b/Wrappers/Python/src/gpu_regularisers.pyx
@@ -157,7 +157,7 @@ def ROFTV2D(np.ndarray[np.float32_t, ndim=2, mode="c"] inputData,
regularisation_parameter,
iterations ,
time_marching_parameter,
- dims[0], dims[1], 1);
+ dims[1], dims[0], 1);
return outputData
@@ -210,7 +210,7 @@ def FGPTV2D(np.ndarray[np.float32_t, ndim=2, mode="c"] inputData,
methodTV,
nonneg,
printM,
- dims[0], dims[1], 1);
+ dims[1], dims[0], 1);
return outputData
@@ -266,7 +266,7 @@ def SBTV2D(np.ndarray[np.float32_t, ndim=2, mode="c"] inputData,
tolerance_param,
methodTV,
printM,
- dims[0], dims[1], 1);
+ dims[1], dims[0], 1);
return outputData
@@ -325,7 +325,7 @@ def FGPdTV2D(np.ndarray[np.float32_t, ndim=2, mode="c"] inputData,
methodTV,
nonneg,
printM,
- dims[0], dims[1], 1);
+ dims[1], dims[0], 1);
return outputData
@@ -381,7 +381,7 @@ def NDF_GPU_2D(np.ndarray[np.float32_t, ndim=2, mode="c"] inputData,
# Run Nonlinear Diffusion iterations for 2D data
# Running CUDA code here
- NonlDiff_GPU_main(&inputData[0,0], &outputData[0,0], regularisation_parameter, edge_parameter, iterationsNumb, time_marching_parameter, penalty_type, dims[0], dims[1], 1)
+ NonlDiff_GPU_main(&inputData[0,0], &outputData[0,0], regularisation_parameter, edge_parameter, iterationsNumb, time_marching_parameter, penalty_type, dims[1], dims[0], 1)
return outputData
def NDF_GPU_3D(np.ndarray[np.float32_t, ndim=3, mode="c"] inputData,
--
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